It has been proven to be advantageous—and we recommend it—to accompany all forms of biodemographic studies with a control population. This has a simple reason. Carey (2000) emphasized how difficult it is to speak on life span in general and, in particular, in insects. In contrast to life expectancy and age specific
Days dx qx log qx x: age interval (days); Zx: survivors at the beginning of age interval; dx: deads during the age interval (absolute death rate); qx: age-specific death rate; ex: life expectancy and a = number of days in the age interval dx = 'x - '(x+1)
. + Lw = E Lx mortality, which are measurable values, "life span'' is weakly defined as time after which no member of a given species can survive even under the most favorable conditions. ''Maximum life-span potential'' is another description. It is evident therefore that maximum life span depends on the number of individuals under observation; it is higher when large numbers of individuals are observed. On the other hand, data on longevity obtained under laboratory conditions may have nothing to do with data recorded under free-living conditions. The determination of maximum life spans of ectothermic organisms as insects is even more problematical. Insects are extremely sensible to abiotic factors like temperature, humidity or light regime. It is therefore meaningless— as Carey pointed out—''to consider life-span for any species without considering environmental, ecological and evolutionary contexts.''
Preparing mortality data To get survival and mortality data of Phormia in a longitudinal study, we start with a population of 400 individuals. Dead flies are counted daily, and mortality statistics are calculated after scaling the data to 1000. (Table 21.1; see Lamb, 1977).
Plotting the logarithm of qx against age in days results in the Gompertz curve of mortality.
It is easy to put the single calculation steps into an Excel table, so that you only have to count the dead flies per day.
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